SBIR Phase II: Filmmaking for Everyone: Computational Video Editing

SBIR 第二阶段：适合所有人的电影制作：计算视频编辑

• 批准号: 1950115
• 负责人: Genevieve Patterson
• 金额: $ 74.86万
• 依托单位: TRASH INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2020-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1950115&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Filmmaking; Everyone

The broader impacts of this Small Business Innovation Research (SBIR) Phase II project enable improved user-generated video content. Video online platforms have radically changed how people communicate, learn, and inspire. Unfortunately, many potentially inspiring videos are lost or never shared due to an inability to edit them into compelling vignettes. Most tools for editing video are expensive, difficult to learn, and time-consuming. This project’s research enables consumers or nascent businesses to make polished, professional videos with a single phone click through the use of computational cinematography and techniques from deep learning and artificial intelligence (AI). The delivered software solution will produce high-quality edited footage within minutes, compared with a human editor requiring hours. This project combines the analysis of video using computer vision with editing algorithms to empower new creators to participate in this fast-growing medium. This Small Business Innovation Research (SBIR) Phase II project will produce AI-powered software for automatically editing raw video footage into quality short films on a mobile phone platform. The proposed project will integrate advanced computational video manipulation, computer vision, and audio recognition. The prototype AI editor will select relevant content from source footage and synchronize it to music, using only the restricted computational resources of a typical mobile platform. The AI makes decisions based on the video content, the music content, and narrative editing styles learned from a large dataset of similar films. This project will deliver AI-based editing technology that trims and arranges input footage based on the spoken dialogue in the input videos.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响，使改进的用户生成的视频内容。视频在线平台从根本上改变了人们沟通、学习和激励的方式。 不幸的是，许多潜在的鼓舞人心的视频丢失或从未共享，由于无法编辑成引人注目的小插曲。大多数编辑视频的工具都很昂贵，很难学习，而且很耗时。该项目的研究使消费者或新兴企业能够通过使用计算电影摄影和深度学习和人工智能（AI）技术，只需点击一次手机即可制作精美的专业视频。交付的软件解决方案将在几分钟内生成高质量的编辑画面，而人工编辑则需要数小时。 该项目将使用计算机视觉的视频分析与编辑算法相结合，使新的创作者能够参与这个快速增长的媒体。这个小企业创新研究（SBIR）第二阶段项目将生产人工智能驱动的软件，用于在移动的手机平台上自动将原始视频剪辑成高质量的短片。 拟议的项目将集成先进的计算视频处理，计算机视觉和音频识别。 原型AI编辑器将从源片段中选择相关内容并将其同步到音乐，仅使用典型移动的平台的有限计算资源。人工智能根据视频内容、音乐内容和从类似电影的大型数据集中学习到的叙事编辑风格做出决策。该项目将提供基于人工智能的编辑技术，根据输入视频中的语音对话对输入视频进行修剪和排列。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。